You can now use upgraded versions of Apache MXNet, TensorFlow, CNTK, and Caffe, on the AWS Deep Learning AMI v1.2 for Ubuntu, including Keras, available in the AWS Marketplace. The Deep Learning AMI v1.2 for Ubuntu is designed to continue to provide a stable, secure, and high performance execution environment for deep learning applications running on Amazon EC2. The latest MXNet release (v0.9.3), included with this AMI v1.2, adds several enhancements including a faster new image processing API that enables parallel processing, improved multi GPU performance, and support for new operators. This AMI includes the following framework versions: Apache MXNet: v0.9.3; Tensorflow v1.0.0; Caffe release: rc5; Theano: rel 0.8.2; Keras: 1.2.2; CNTK: v2.0 beta12.0; and Torch: master branch. The Deep Learning AMI includes Jupyter notebooks with Python 2.7 and Python 3.4 kernels, Matplotlib, Scikit-image, CppLint, Pylint, pandas, Graphviz, Bokeh Python packages, Boto and Boto 3 and the AWS CLI. The DL AMI also comes packaged with Anaconda 2 and Anaconda 3 Data Science platform. You can start using the Deep Learning AMI release v1.2 in the AWS Marketplace, today.

In addition, the AWS CloudFormation Deep Learning template has now been updated with additional capabilities. This template now lets you select GPU or CPU instance types and choose between the Ubuntu or Amazon Linux Deep Learning AMI for your cluster. You can also provision a new Amazon EFS to your cluster, or attach an one, to let you easily share code, data, logs, and results. To learn more, visit the github repo and follow the tutorial to see how easy it is to run distributed training on AWS using Apache MXNet and Tensorflow frameworks.